Turn Kannada audio
till text you can trust.

A different approach to Kannada transcription.

Kannada is spoken by more than 40 million people, mostly across Karnataka but also across communities in the US, Pakistan, and Singapore. It is one of the oldest languages still in active use, with written records dating back to the 5th century AD, and it carries two well-known dialects, Halakki and Gokak, plus a grammar structure that trips up most generic transcription tools. Turning Kannada speech into usable text has always meant either a bilingual transcriber working by hand, or software that gets the words roughly right and drops everything else.

Where Kannada transcription usually breaks down

Most transcription tools are tuned for a handful of high-resource languages, and Kannada rarely gets the same attention. Speakers get misheard, technical or regional terms get flattened into nonsense, and tone, hesitation, or emphasis in the recording never make it into the transcript at all. Teams end up correcting entire passages by hand, which erases most of the time an automated tool was supposed to save.

Reading the recording, not just the words

Speak AI transcribes Kannada audio and video with speaker labels and timestamps, then reads the recording itself: who is speaking, when they switch between Kannada and English mid-sentence, and how the delivery changes across a long interview or hearing. Names, terms, and callback details are extracted into structured fields your team can search and query. Then you can ask across your entire Kannada archive with AI chat, using ChatGPT, Claude, and Gemini built directly into the workspace.

• Kannada audio and video, transcribed with speaker labels and translation into English or another language.
• Supports both major dialects, Halakki and Gokak, alongside standard written Kannada.
• Captions and subtitles (SRT, VTT) generated straight from the timestamped transcript.
• Export to Word, PDF, TXT, CSV, or JSON, depending on how your team needs to use it.

From one file to a searchable archive

The result is a Kannada archive that behaves like a well-run English one. Interviews, hearings, and support calls become searchable text instead of a folder of audio files nobody has time to relisten to, and dashboards you can customize and white-label track themes and volume across your Kannada recordings over time. One multilingual education platform put its assessment recordings through this kind of workflow across embedded recorders spanning multiple languages, without hiring reviewers for each one.

And because Kannada recordings rarely live in isolation from the rest of your work, the same engine scores calls and coaches teams on the same criteria, connecting Kannada transcription to call scoring and the wider kunskapsbas your team already runs on.